Structural Adaptations of Decentralized Coordination Processes in Self-Organizing Systems

2016 ◽  
Author(s):  
Thomas Preisler ◽  
Tim Dethlefs ◽  
Wolfgang Renz
Keyword(s):  
Decentralized Coordination ◽  
Structural Adaptations ◽  
Self Organizing

Self-organizing Mobile Sensor Network

2011 ◽  
pp. 558-583
Author(s):  
Geunho Lee ◽  
Nak Young Chong
Keyword(s):  
Mobile Robots ◽  
Large Scale ◽  
Triangle Mesh ◽  
Unified Framework ◽  
Decentralized Coordination ◽  
Physical Environments ◽  
Spatially Distributed ◽  
Constrained Environments ◽  
Robotic Sensors ◽  
Self Organizing

Ambient Intelligence (AmI) is a multidisciplinary approach aimed at enriching physical environments with a network of distributed devices, such as sensors, actuators, and computational resources, in order to support humans in achieving their everyday task. Within the framework of AmI, this chapter presents decentralized coordination for a swarm of autonomous robotic sensors building intelligent environments adopting AmI. The large-scale robotic sensors are regarded as a swarm of wireless sensors mounted on spatially distributed autonomous mobile robots. Therefore, motivated by the experience gained during the development and usage for decentralized coordination of mobile robots in geographically constrained environments, our work introduces the following two detailed functions: self-configuration and flocking. In particular, this chapter addresses the study of a unified framework which governs the adaptively self-organizing processes for a swarm of autonomous robots in the presence of an environmental uncertainty. Based on the hypothesis that the motion planning for robot swarms must be controlled within the framework, the two functions are integrated in a distributed way, and each robot can form an equilateral triangle mesh with its two neighbors in a geometric sense. Extensive simulations are performed in two-dimensional unknown environments to verify that the proposed method yields a computationally efficient, yet robust deployment.

Modeling student knowledge with self-organizing feature maps.

1993 ◽  
Author(s):  
Steven A. Harp ◽  
Tariq Samad ◽  
Michael Villano
Keyword(s):  
Feature Maps ◽  
Student Knowledge ◽  
Self Organizing

Art as a Self-Organizing Complex System

1998 ◽  
Author(s):  
Svetlana Apenova ◽  
Igor Yevin
Keyword(s):  
Complex System ◽  
Self Organizing

Gestalt Self-Organizing Forces in Visual Memory

1992 ◽  
Author(s):  
Lewis O. Harvey ◽  
Anne Igel ◽  
Eric K. Schmidt
Keyword(s):  
Visual Memory ◽  
Self Organizing

Towards Self-Organizing Economy

2006 ◽  
Author(s):  
Elena Pugacheva ◽  
Konstantin Solovienko
Keyword(s):  
Self Organizing

Application of Fractal Methods to Ensure the Cyber-Resilience of Self-Organizing Networks

2019 ◽  
Vol 22 (4) ◽  
pp. 336-341
Author(s):  
D. V. Ivanov ◽  
D. A. Moskvin
Keyword(s):  
Information Security ◽  
Network Structure ◽  
Self Regulation ◽  
Security Threats ◽  
Self Organizing Networks ◽  
Self Organizing ◽  
Fractal Methods

In the article the approach and methods of ensuring the security of VANET-networks based on automated counteraction to information security threats through self-regulation of the network structure using the theory of fractal graphs is provided.

Auscultating Diagnosis for Hemodialysis Shunt Stenosis using a Self-Organizing Map and Hidden Markov Model

2012 ◽  
Vol 132 (10) ◽  
pp. 1589-1594 ◽  
Author(s):  
Hayato Waki ◽  
Yutaka Suzuki ◽  
Osamu Sakata ◽  
Mizuya Fukasawa ◽  
Hatsuhiro Kato
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Self Organizing Map ◽  
Self Organizing
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